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Stock market index prediction using artificial neural network

Author

Listed:
  • Hedayati , Amin

    (Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran)

  • Hedayati , Moein

    (Faculty of Managing and Accounting, College of Farabi, University of Tehran, Qom, Iran)

  • Esfandyari, Morteza

    (Department of Chemical Engineering, Faculty of Engineering, University of Bojnord, Bojnord, Iran)

Abstract

In this study the ability of artificial neural network(ANN) in forecasting the daily NASDAQ stock exchange rate was investigated. Several feed forward ANNs that were trained by the back propagation algorithm have been assessed. The methodology used in this study considered the short-term historical stock prices as well as the day of week as inputs. Daily stock exchange rates of NASDAQ from January 28, 2015 to 18 June, 2015 are used to develop a robust model. First 70 days (January 28 to March 7) are selected as training dataset and the last 29 days are used for testing the model prediction ability. Networks for NASDAQ index prediction for two type of input dataset (four prior days and nine prior days) were developed and validated.

Suggested Citation

  • Hedayati , Amin & Hedayati , Moein & Esfandyari, Morteza, 2016. "Stock market index prediction using artificial neural network," Journal of Economics, Finance and Administrative Science, Universidad ESAN, vol. 21(41), pages 89-93.
    • Handle: RePEc:ris:joefas:0104
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    More about this item

    Keywords

    NASDAQ; ANN; Predicción;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models

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